Elastic vs. Splunk for logs, security, and observability

The right observability and security solution is fast, affordable, and built for the future of generative AI.

Review the key differences between the Elastic and Splunk data tiers

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Say goodbye to Splunk limitations — elevate observability with Elastic

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Stay ahead of threats. Empower your teams with AI-driven security analytics.

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Your peers cut costs by migrating from Splunk to Elastic

  • 85
    %

    reduction in time spent identifying and resolving incidents, realized by a leading multinational telecommunication (400TB ingested a day).

  • $27M

    total annual benefits realized by a leading financial services company by migrating from Splunk to Elastic.

  • 50
    %

    reduction in costs compared with Splunk, through more efficient data management.

Elastic vs. Splunk: Key differences

Elastic

Splunk

User experience

Fully unified user interface, for observability and security on the same Elastic Search AI Platform.
Splunk's fragmented offerings include Splunk Enterprise, Splunk Cloud, Splunk Security, and Splunk Observability Cloud. Splunk's acquisitions don't integrate well, creating siloed solutions that are an obstacle to speedy problem resolution.

Insights

Advanced search and generative AI capabilities, including vector search, natural language processing (NLP), a generative AI Assistant powered by RAG, AI-powered Attack Discovery, an open library of ML models, and easily customizable ML jobs for any type of data or use case.
Lack of advanced AI and analytics capabilities, hampered by disjointed data sets.

Pricing

Simple pricing based only on the resource you use. With Elastic, a single SKU provides all features across observability, security, and search.
Each Splunk product has a different pricing model. And you have to purchase multiple solutions and add-ons to achieve full-stack observability. Volume and compute-based pricing options add further complexity and costs.

Storage and performance

A unified data store for all data (logs, metrics, traces, profiling, security events, business data etc.) with fast, cost-effective access, even from archival storage tiers (without rehydration). Plus, rapidly search and get insights — no matter where your data is located.

Splunk's fragmented solution architecture results in disjointed data sets (e.g., log data siloed from metrics and traces). Further, Splunk's data tiering approach effectively has a higher cost:performance ratio compared to the Elastic equivalent, with the lowest-cost tiers requiring rehydration (24hr) to access.

Query language

ES|QL is Elastic's piped query language and engine that addresses many of the previous constraints around its JSON-based DSL queries.
Splunk's piped query language, SPL, allows you to search and manipulate Splunk data.

User experience

Insights

Pricing

Storage and performance

Query language

Elastic

Splunk

Fully unified user interface, for observability and security on the same Elastic Search AI Platform.
Splunk's fragmented offerings include Splunk Enterprise, Splunk Cloud, Splunk Security, and Splunk Observability Cloud. Splunk's acquisitions don't integrate well, creating siloed solutions that are an obstacle to speedy problem resolution.
Advanced search and generative AI capabilities, including vector search, natural language processing (NLP), a generative AI Assistant powered by RAG, AI-powered Attack Discovery, an open library of ML models, and easily customizable ML jobs for any type of data or use case.
Lack of advanced AI and analytics capabilities, hampered by disjointed data sets.
Simple pricing based only on the resource you use. With Elastic, a single SKU provides all features across observability, security, and search.
Each Splunk product has a different pricing model. And you have to purchase multiple solutions and add-ons to achieve full-stack observability. Volume and compute-based pricing options add further complexity and costs.
A unified data store for all data (logs, metrics, traces, profiling, security events, business data etc.) with fast, cost-effective access, even from archival storage tiers (without rehydration). Plus, rapidly search and get insights — no matter where your data is located.

Splunk's fragmented solution architecture results in disjointed data sets (e.g., log data siloed from metrics and traces). Further, Splunk's data tiering approach effectively has a higher cost:performance ratio compared to the Elastic equivalent, with the lowest-cost tiers requiring rehydration (24hr) to access.

ES|QL is Elastic's piped query language and engine that addresses many of the previous constraints around its JSON-based DSL queries.
Splunk's piped query language, SPL, allows you to search and manipulate Splunk data.

See why companies — like yours — choose Elastic

Learn about the real-world benefits of using the Elastic Search AI Platform for observability and security.

  • Informatica cuts costs, accelerates MTTR, and stays one step ahead of threats to system performance — all with a unified observability and security solution.

  • Booking.com protects its brand with a truly integrated security and observability solution that automates data gathering, analysis, detection, and response.

  • Comcast enables its engineers to iterate and innovate faster with essential feedback from Elastic Observability.

Splunk Replacement for Data Management

Elastic vs. Splunk: Cold truth about data tiers

To be successful with Splunk — you need dedicated resources plus a near-term and long-term storage strategy. Many Splunk customers struggle to align their evolving business needs to the correct data storage option.

But with Elastic, you get simple, straight-forward, and centralized data management — with no hidden agenda or costs. Search across geos in milliseconds, not seconds. Query archival tiers in minutes, not hours. Compare the capabilities of Splunk versus Elastic data tiers so you can make an informed, cost-effective decision.

Splunk Replacement for Logging

Elastic Observability

In Splunk, logs are fragmented and separated from traces and metrics. Teams cannot see the full picture on one screen. Take the first step by consolidating your logs on Elastic and gain the benefits of a unified observability solution built with search AI. With end-to-end visibility across all your logs, metrics, and traces, correlated and in context, you can decrease mean time to resolution (MTTR) and lower total cost of ownership (TCO).

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Splunk Replacement for SIEM

Elastic Security

Many legacy SIEMs, like Splunk, weren't built to adjust to your business' needs. AI-driven security analytics is critical to adapt to the latest breed of threat types. Accelerate SecOps workflows and reduce risk with Elastic. You get limitless scalability, advanced analytics, and generative AI insights, to eliminate blind spots and strengthen defenses to help you address the global cyber skills shortage. The AI revolution is here — and SIEM will never be the same.

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